Assembly of quantitative models of large complex networks brings about several challenges.
One of them is the combinatorial complexity, where relatively few signalling molecules can …

All processes of life are controlled by networks of interacting biochemical components. The
purpose of modelling these networks is manifold. From a theoretical point of view it allows …

Background: Receptors and scaffold proteins possess a number of distinct domains and
bind multiple partners. A common problem in modeling signaling systems arises from a …

Background Combinatorial complexity is a challenging problem for the modeling of cellular
signal transduction since the association of a few proteins can give rise to an enormous …

Biochemical network modeling and simulation is an essential task in any systems biology
project. The systems biology markup language (SBML) was established as a standardized …

Interactions among cellular constituents play a crucial role in overall cellular function and
organization. These interactions can be viewed as being complementary to the usual “parts …

Rule-based modeling has become a powerful approach for modeling intracellular networks,
which are characterized by rich molecular diversity. Truly comprehensive models of cell …

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When
modelling or redesigning such systems, functional subsystems are often analysed …

Mathematical dynamical models of intracellular signaling networks are continuously
increasing in size and model complexity due in large part to the data explosion in biology …

Modelling and simulation techniques are valuable tools for the understanding of complex
biological systems. The design of a computer model necessarily has many diverse inputs …